Machine Learning, Winter School, HPC Lab., 2020

<01/02>

  • Week 1 - Introduction, Linear Regression with One Variable

  • Week 2 - Linear Regression with Multiple Variables, Octave Tutorial

<01/09>

  • Week 3 - Logistic Regression, Regularization

<01/16>

  • Week 4 - Neural Networks: Representation

<01/23>

  • Week 5 - Neural Networks: Learning

<01/30>

  • Week 6 - Evaluating a Learning Algorithm

<02/06>

  • Week 7 - Support Vector machines

<02/13>

  • Week 8 - Unsupervised Learning, Dimensionality Reduction

<02/20>

  • Week 9 - Anomaly Detection, Recommender Systems

    • Summary - Slides / Video (by Jaehong Lee)

    • Commentary for Test - Slides / Video (by Homin Kang)

    • Commentary for PA - Slides / Video (by Sangwon Choi)